Information overload is a state of being overwhelmed by the amount of data presented for one’s attention or processing. An excessive amount of information may be available to a customer to help him or her make a decision, complete a task, or answer a question. This excessive information impedes the decision-making process and even causes increasing levels of stress and anxiety.
In essence, data overload refers to a cognitive process in which people have a difficult time making a decision when faced with many options. The idea is that, by reducing consumer choices you can create a better lived experience for shoppers.
Why Is Collecting eCommerce Data Necessary?
At this moment in time, data and information collecting is essential to the eCommerce industry. Customer data crosses the line between understanding your customer base and not knowing them at all.
Relevant data can be used in a multitude of ways, ranging from coaching sales team employees to winning your customers’ trust. In 2020, over two billion people purchased goods or services online. With the number expected to rise each year, it makes sense to use data to improve your strategy. Managing data overload starts with building strong marketing foundations, including knowing what to measure.
How to Avoid Data Overload
- Reduce the choice overload
Having too many choices isn’t a good thing; customers tend to buy less and feel dissatisfied when they do buy.
When it comes to the business of selling, whether it’s a set of products or a bundle of services, it’s important to reduce any amount of mental strain that customers can experience when presented with a lot of choices. When fine-tuning specific elements on your website, newsletter, and other marketing platforms, there is a bigger chance of increasing conversions and sales.
- Reduce data redundancy
Entering information is a time-consuming process for your employees, so lessening the amount of useless data they need to input can benefit them immensely. Cut out any unnecessary data, so that only useful data is processed. One of the best ways to do this is by regularly reviewing and revising your forms and documents to check that all the requested data is relevant and necessary for your business processes.
- Standardize processes
Standardizing both your data collection and data entry processes helps improve overall accuracy and consistency. By maintaining standard processes, your employees know what to expect and look for with each form, and they know what protocols to follow. This helps them fall into a pattern of operation, allowing them to work both quickly and accurately. In addition to being helpful for your employees, standardization is necessary if you’re looking to automate any of your data entry processes.
- Understand the purpose behind data collection
For every data collection operation, you should discuss the following with the team in charge:
- What is the goal of collecting this set of data?
- What KPIs can be used/do you use to measure whether the goal is being met?
- How does this goal integrate into the big picture for your team?
- What beneficial impact does it have in the long term on the customer relationship?
- Shift to a customer-centric perspective
Remind your colleagues that this data collection is one of the many touch points between the brand and the prospect, and go on with the following:
- What do they expect from this interaction and at which step of the customer journey does it happen?
- What value do they provide to their prospects/customers in exchange for their data?
- Will the data collected directly contribute to increasing the value of what they offer?
- How are customers likely to perceive it?
For example, asking for your customer location will not be perceived the same if you ask during checkout in order to locate the nearest relay point, or out of nowhere when entering the website. The request for access to personal data is an integral part of the user experience, and having designers on board can shed interesting light on the consistency between what the team wants to offer, and the perceived value.
- Set up a data collection workflow
In most cases, you will need to get consent from your visitors to collect their personal data. Consent collection is part of the implementation, and will give you valuable information about how your prospects perceive your data collection strategy. The collection workflow should be adapted to the specificity of the target audience (platforms used, relationship with the brand, sensitivity to collection issues, and interest for a customized experience…) and must be able to evolve rapidly according to feedback.
- Start with the easier choices
Starting with the easier choices, containing fewer options, and then moving on to the more difficult ones, containing more options, can also decrease data overload. It will help build momentum and confidence. When customers have invested time in making a few choices, they are more likely to see the value of completing the task and less likely to give up
- Use Product Information Management (PIM) systems
Implement a PIM system that centralizes product data and allows for easy management, updating, and distribution of product information across various platforms.
- Prioritize data quality over quantity
Focus on collecting and entering accurate and relevant data rather than overwhelming your database with unnecessary information. Quality trumps quantity in e-commerce data management.
Data overload damages the revenue sources of the company. Information overload is a real phenomenon which prevents you from taking decisions or actions because you feel you have too much information to consume. Following the above-mentioned tips will reduce the information overload and would lead to efficient eCommerce data entry.
Having a reliable team for data encoding and monitoring allows you to prevent data overload. If you are looking for a cost-efficient option, consider hiring a company that outsources data entry.
You can enjoy the flexibility and expertise that a data entry partner can provide. You will also be able to set your targets and standards for processing data. Data entry outsourcing could be the key to preventing data overload.